Using SABC Algorithm for Scheduling Unrelated Parallel Batch Processing Machines Considering Deterioration Effects and Variable Maintenance

Using SABC Algorithm for Scheduling Unrelated Parallel Batch Processing Machines Considering Deterioration Effects and Variable Maintenance

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This paper investigates the problem of processing jobs on unrelated parallel batch machines, taking into account job arrival times, machine deterioration effects, and variable preventive maintenance (VPM).To address this complex scheduling problem, this paper proposes a Self-Adaptive Artificial Bee Colony (SABC) algorithm, incorporating an adaptive variable Building Set neighborhood search mechanism into the algorithm.To verify the effectiveness of the proposed algorithm, we designed comparative experiments, comparing the SABC algorithm with the NSGA-III algorithm on Cushion problem instances of different scales.The results indicate that the SABC algorithm outperforms the NSGA-III algorithm in terms of solution quality and diversity, and this advantage becomes more pronounced as the problem scale increases.